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Smoothing
Known as:
Smooth-down
, Smoothes down
, Smoothing (disambiguation)
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In statistics and image processing, to smooth a data set is to create an approximating function that attempts to capture important patterns in the…
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Related topics
Related topics
48 relations
Additive model
Additive smoothing
Algorithm
Bilateral filter
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Broader (1)
Signal processing
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2019
Highly Cited
2019
When Does Label Smoothing Help?
Rafael Müller
,
Simon Kornblith
,
Geoffrey E. Hinton
Neural Information Processing Systems
2019
Corpus ID: 174802983
The generalization and learning speed of a multi-class neural network can often be significantly improved by using soft targets…
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Highly Cited
2019
Highly Cited
2019
Certified Adversarial Robustness via Randomized Smoothing
Jeremy M. Cohen
,
Elan Rosenfeld
,
J. Z. Kolter
International Conference on Machine Learning
2019
Corpus ID: 59842968
We show how to turn any classifier that classifies well under Gaussian noise into a new classifier that is certifiably robust to…
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Highly Cited
2015
Highly Cited
2015
Rethinking the Inception Architecture for Computer Vision
Christian Szegedy
,
Vincent Vanhoucke
,
Sergey Ioffe
,
Jonathon Shlens
,
Z. Wojna
Computer Vision and Pattern Recognition
2015
Corpus ID: 206593880
Convolutional networks are at the core of most state of-the-art computer vision solutions for a wide variety of tasks. Since 2014…
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Highly Cited
2013
Highly Cited
2013
Bayesian Filtering and Smoothing
Simo Särkkä
Institute of Mathematical Statistics textbooks
2013
Corpus ID: 32945148
Filtering and smoothing methods are used to produce an accurate estimate of the state of a time-varying system based on multiple…
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Highly Cited
2008
Highly Cited
2008
iSAM: Incremental Smoothing and Mapping
M. Kaess
,
Ananth Ranganathan
,
F. Dellaert
IEEE Transactions on robotics
2008
Corpus ID: 1312251
In this paper, we present incremental smoothing and mapping (iSAM), which is a novel approach to the simultaneous localization…
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Highly Cited
2005
Highly Cited
2005
Smooth minimization of non-smooth functions
Y. Nesterov
Mathematical programming
2005
Corpus ID: 2391217
Abstract.In this paper we propose a new approach for constructing efficient schemes for non-smooth convex optimization. It is…
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Highly Cited
2005
Highly Cited
2005
Scalable collaborative filtering using cluster-based smoothing
Gui-Rong Xue
,
Chenxi Lin
,
+4 authors
Zheng Chen
Annual International ACM SIGIR Conference on…
2005
Corpus ID: 2801577
Memory-based approaches for collaborative filtering identify the similarity between two users by comparing their ratings on a set…
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Highly Cited
1996
Highly Cited
1996
An Empirical Study of Smoothing Techniques for Language Modeling
Stanley F. Chen
,
Joshua Goodman
Annual Meeting of the Association for…
1996
Corpus ID: 215842252
We present an extensive empirical comparison of several smoothing techniques in the domain of language modeling, including those…
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Review
1985
Review
1985
Exponential smoothing: The state of the art
E. S. Gardner
1985
Corpus ID: 62343563
This paper is a critical review of exponential smoothing since the original work by Brown and Holt in the 1950s. Exponential…
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Highly Cited
1967
Highly Cited
1967
Smoothing by spline functions
C. Reinsch
1967
Corpus ID: 26555189
In this paper we generalize the results of [4] and modify the algorithm presented there to obtain a better rate of convergence.
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